RAG is a very useful flow but I agree the complexity is often overwhelming, esp as you move from a toy example to a real production deployment. It's not just ch

RAG is a very useful flow but I agree the complexity is often overwhelming, esp as you move from a toy example to a real production deployment. It's not just choosing a vector DB (last time I checked there were about 50), managing it, deciding on how to chunk data, etc. You also need to ensure your retrieval pipeline is accurate and fast, ensuring data is secure and private, and manage the whole thing as it scales. That's one of the main benefits of using Vectara (https://vectara.com https://vectara.com; FD: I work there) - it's a GenAI platform that abstracts all this complexity away, and you can focus on building your application.